Vibration-based multi-class fault severity classification of wind turbine gearboxes using explainable machine learning

This study presents a comprehensive fault severity classification framework for wind turbine (WT) gearboxes using vibration data from the National Renewable Energy Laboratory. The objective is to identify the extent of damage, categorized as early, moderate, or severe, based on analysis of vibration...

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Λεπτομέρειες βιβλιογραφικής εγγραφής

Κύριοι συγγραφείς:	All Mumtahina Arika, A.S. Nazmul Huda, Shameem Ahmad, Amirul Islam
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	Elsevier 2026-05-01
Σειρά:	Energy Conversion and Management: X
Θέματα:	Wind Turbine Gearbox Damage Severity Classification eXplanable AI (XAI) SHapley Additive exPlanations (SHAP)
Διαθέσιμο Online:	http://www.sciencedirect.com/science/article/pii/S2590174526001042
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